The most effective machine learning techniques
You'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.
Course Outline:
- Silicon Valley's best practices in innovation as it pertains to machine learning and AI.
- Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks)
- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning)
- Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI)
- How to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas
*Stanford University 在全球大學排名第4位 (資料來源：Times Higher Education (THE) World University Rankings 2020).
